databricks-cli/libs/template/templates/default-python/template/{{.project_name}}/README.md.tmpl

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# {{.project_name}}
The '{{.project_name}}' project was generated by using the default-python template.
## Getting started
1. Install the Databricks CLI from https://docs.databricks.com/dev-tools/cli/databricks-cli.html
2. Authenticate to your Databricks workspace, if you have not done so already:
```
$ databricks configure
```
3. To deploy a development copy of this project, type:
```
$ databricks bundle deploy --target dev
```
(Note that "dev" is the default target, so the `--target` parameter
is optional here.)
This deploys everything that's defined for this project.
For example, the default template would deploy a job called
`[dev yourname] {{.project_name}}_job` to your workspace.
You can find that job by opening your workpace and clicking on **Workflows**.
4. Similarly, to deploy a production copy, type:
```
$ databricks bundle deploy --target prod
```
Note that the default job from the template has a schedule that runs every day
(defined in resources/{{.project_name}}_job.yml). The schedule
is paused when deploying in development mode (see
https://docs.databricks.com/dev-tools/bundles/deployment-modes.html).
5. To run a job or pipeline, use the "run" command:
```
$ databricks bundle run
```
6. Optionally, install developer tools such as the Databricks extension for Visual Studio Code from
https://docs.databricks.com/dev-tools/vscode-ext.html.
{{- if (eq .include_python "yes") }} Or read the "getting started" documentation for
**Databricks Connect** for instructions on running the included Python code from a different IDE.
{{- end}}
7. For documentation on the Databricks asset bundles format used
for this project, and for CI/CD configuration, see
https://docs.databricks.com/dev-tools/bundles/index.html.